A novel detection method of spray droplet distribution based on LIDARs

Zheng Yongjun, Yang Shenghui, Yubin Lan, Clint Hoffmann, Zhao Chunjiang, Chen Liping, Liu Xingxing, Tan Yu

Abstract


During the process of plant protection in agriculture, the distribution and deposition of droplets or fog fields could directly influence the effectiveness and efficiency of spray. The traditional method of measurement of the distribution of droplets mainly used water sensitive papers, glass containers or flour to collect data and inverse results, while a new method of measurement based on the principle of reflection of LIDAR was presented. Droplets were the major targets of the study, and four important algorithms were primarily developed, including the recognition and extraction of targets, the superposition in time-domain, the calculation of effective ranges of distribution, and the development of 3D distribution models. Combined with these algorithms, in order to eliminate the environmental noise, the methods of Fuzzy Environment Matching and Secondary Filter were created and utilized. Meanwhile, the statistics was used for analysis of the duration of scanning as well as computation of the distribution, with enough datasets but the minimum length of time. The results of the experiments showed that the relative error of measurement was less than 7% and Relative Standard Deviation was less than 16%, compared with the values of manual measurement. Furthermore, the 3D models were accurate and clarified in the wind-tunnel experiment. The completed system based on this method could adapt to the requirements of both indoor and outdoor detection. Besides, it is capable of the quantized detection of droplet distribution, providing an effective way of tests for spray technique, especially for the research of the application of plant protection by UAVs.
Keywords: droplets, distribution, detection, agricultural aviation, UAV
DOI: 10. 25165/j.ijabe.20171004.3118

Citation: Zheng Y J, Yang S H, Lan Y B, Hoffmann C, Zhao C J, Chen L P, et al. A novel detection method of spray droplet distribution based on LIDARs. Int J Agric & Biol Eng, 2017; 10(4): 54–65.

Keywords


droplets, distribution, detection, agricultural aviation, UAV

Full Text:

PDF

References


Qin W C, Xue X Y, Zhou L X, Zhang S C, Sun Z, Kong W, et al. Effects of spraying parameters of unmanned aerial vehicle on droplets deposition distribution of maize canopies. Transactions of the CSAE, 2014; 30(5): 50–56. (in Chinese )

Zhang P, Deng L, Lyu Q, He S L, Yi S L, Liu Y D, et al. Effects of citrus tree-shape and spraying height of small unmanned aerial vehicle on droplet distribution. Int J Agric & Biol Eng, 2016; 9(4): 45–52.

Ru Y, Jin L, Zhou H P, Jia Z C. Charging characteristics of droplets effect on the distribution and adhesion of droplets on target. Journal of Nanjing Forestry University (Natural Sciences Edition), 2014; 38(3): 129–133. (in Chinese)

Song S R, Hong T S, Wang W X, Zhang H X, Luo X W, Francis S. Testing analysis on deposit and distribution of pesticide spraying in rice fields. Transactions of the CSAM, 2004; 35(6): 90–93. (in Chinese )

Zheng Y J, Yang S H, Zhao C J, Chen L P, Lan Y B, Tan Y. Modelling operation parameters of UAV on spray effects at different growth stages of corns. Int J Agric & Biol Eng, 2017; 10(3): 57–66.

Qin W C, Xue X Y, Cui L F, Zhou Q Q, Xu Z F, Chang F L. Optimization and test for spraying parameters of cotton defoliant sprayer. Int J Agric & Biol Eng, 2016; 9(4): 63–72.

Bonds J A, Mulla C, Hunter E. Characterization of the effects of droplet size, air blast strength, and angle on spray distribution and efficacy of a buffalo turbine barrier treatment sprayer. Journal of ASTM International, 2011; 8(5): 1–6.

Wolf R E. Comparing downwind spray droplet deposits of four flat-fan nozzle types measured in a wind tunnel and analyzed using dropletscan software. Applied Engineering in Agriculture, 2005; 21(2): 173–177.

De Boer D W, Monnens M J, Kincaid D C. Measurement of sprinkler droplet size. Transactions of the ASABE, 2001; 17(1): 11–15.

Guan X P. Effects of Operating Parameters for Unmanned Aerial Vehicles on Spraying Deposition. Hubei Agricultural Sciences, 2014; 53(3): 678–680. (in Chinese).

Qiu B J, Wang L W, Cai D L, Wu J H, Ding G R, Guan X P. Effects of flight altitude and speed of unmanned helicopter on spray deposition uniform. Transactions of the CSAE, 2013; 29(24): 25–32. (in Chinese)

Foqué D, Nuyttens D. Effect of air support and spray angle on coarse droplet sprays in ivy pot plants. Transactions of the ASABE, 2011; 54(2): 409–416.

Qi L J, Hu K Q, Mang L, Wang H T. Droplet detection based on image processing. Transactions of the CSAM, 2009; 40(Supp.1): 48–51. (in Chinese)

Lu J, Li P P, Qiu B J, Jia W D. Analysis of charged droplet characteristics and deposition motion in agricultural high voltage electrostatic spraying field. High Voltage Engineering, 2009; 35(5): 1077–1082. (in Chinese)

Salyani M, Fox R D. Performance of image analysis for assessment of simulated spray droplet distribution. Transactions of the ASAE, 1994; 37(4): 1083–1089.

Zhang H C, Dorr Gary, Zheng J Q, Zhou H P. Wind tunnel experiment of influence on droplet size distribution of flat fan nozzles. Transactions of the CSAM, 2012; 43(6): 53–57. (in Chinese ).

Wedding J B, Kim Y J. Wind tunnel characterization of aerial spray nozzles using the laser particle spectral analyzer. Optical Engineering, 1986; 25(4): 556–560.

Sidahmed M M, Yates W E. Measuring spray droplets with PMS-FSSP probes. Transactions of the ASAE, 1997; 40(5): 1237–1242.

Endalew A M, Debaer C, Rutten N, Vercammen J, Delele M A, Ramon H, et al. A new integrated CFD modelling approach towards air-assisted orchard spraying. Part I. Model development and effect of wind speed and direction on sprayer airflow. Computers and Electronics in Agriculture, 2010; 71(2): 128–136.

Crowe T G, Downey D, Giles D K. Digital device and technique for sensing distribution of spray deposition. Transactions of the ASAE, 2005; 48(6): 2085–2093.

Zheng Y J, Lan Y B, Kang F, Ma C, Chen H, Tan Y. Using laser sensor for measuring crop conditions in precision agriculture. 2013 ASABE Annual International Meeting, 2013: 2595–2602.

Shao Q, Xu T, Yoshino T, Zhao Y, Yang W, Zhu H. Point

cloud online measurement of stored bulk grain. Int J Agric & Biol Eng, 2016; 9(1): 71–78.

Zhao T, Noguchi N, Yang L L, Ishii K, Chen J. Development of uncut crop edge detection system based on laser rangefinder for combine harvesters. Int J Agric & Biol Eng, 2016; 9(2): 21–28.

Wang Y X, Xu S S, Li W B, Kang F, Zheng Y J. Identification and location of grapevine sucker based on information fusion of 2D laser scanner and machine vision. Int J Agric & Biol Eng, 2017; 10(2): 84–93.

Zhang Y Y. Zhou J. Laser Radar Based Orchard Trunk Detection. Journal of China Agricultural University, 2015; 20(5): 249–255. (in Chinese)

Xue J L, Zhang S S. Navigation of an agricultural robot based on laser radar. Transactions of the CSAM, 2014; 45(9): 55–60. (in Chinese)

SICK Company. The laser scanning and measurement system: Area scan and profile measurement. 1–62. (in Chinese)




Copyright (c)



2023-2026 Copyright IJABE Editing and Publishing Office